20 3.
Other remains land use types operate in between those settings, where the conversion will occur in specific condition. An example is grassland will be
converted to estate area if estate area is more profitable.
Table 6. Land use conversion matrix for study area
Land Use Future
Water Grassland
Estate Settlement
Forest
P re
sent
Water 1
Grassland 1
1 1
1 Estate
1 1
1 1
Settlement 1
Forest 1
1 1
1 likely to conversion; 0 unlikely to conversion
This method is one of specific setting to determine temporal dynamic of land use simulation. Land use with high investment will not easily be converted to other
uses. Moreover, because of the differences of conversion behavior, dimensionless factor is added to each land use type. This factor represents elasticity conversion,
ranging from 0 easy conversion to 1 irreversible change. Water area and settlement area is an example of this rule, where the elasticity value for urban built
up area is set 1 that shows urban built up area is hard to be converted to another type of land use. Grassland and forest area are more easily to be converted and the
value is 0.4. Estate is set to more difficult to be converted, so the elasticity value is 0.6. The justification of the elasticity values of land uses in this study is based on
field observation and local knowledge and adjustment for the model. The range of values can be seen in following table.
Table 7. Settings of conversion elasticity in the study area
Land Use Type Conversion Elasticity
Water 1
Grassland 0.4
Estate 0.6
Settlement 1
Forest 0.4
Source: Observation and analysis, 2011
21
2.3.3.5. Scenario Setting
The scenarios presented are not necessary the most realistic, but are made in such a way that they provide information on the functioning of the model. A
scenario for the CLUE-S model consists of a file with land requirements and a file that indicates areas where restrictions to conversion apply.
Land Requirements
Land use requirement demand is calculated for every land use in the whole of study area. This requirement becomes a constraint of area needed for simulation.
Demand of land use will be specified in every year by using extrapolation of past land use change trends that have been quantified before year 2001-2009.
Future land utilizations are based on two considerations: 1.
Baseline. Population growth is assumed stable and land requirements of 2009-2020 keep
linear change based on the trend in the period 2001-2009. According to the baseline scenario, the demand of land use year 2009-2020 will be extrapolated
from the annual change in the period 2001-2009. 2.
The increasing growth of population. The assumption is based on a slow growth of population in study area that has
effects on increasing of demand of settlement and estate land use. In this scenario, the demand of urban built-up area is assumed increased twice from
the demand of urban built-up area in baseline scenario.
Spatial Policies
Spatial policies restriction can influence the pattern of land use change. Spatial policies mostly indicate areas where land use changes are restricted through
policies. Besides that, spatial policies can imply stimulation arrangements for a certain land use on a location. In this study, forest designation map is used as area
restriction, where forest area is restricted to be converted into other land use area.
22 Figure 3.
Maps of Restricted Area
Table 8. Scenarios used in spatial modeling
Scenarios Land Requirement
Spatial Policies
First Baseline
Equal with the trend of the land use change in common
No Spatial Policy Second
Equal with the trend of the land use change in common
Forest area is restricted to be converted into other
land use area
Third The increasing growth of
population No Spatial Policy
Fourth The increasing growth of
population Forest area is restricted to
be converted into other land use area
2.3.3. Model Validation
An important stage in the development of any predictive change model is validation. Typically, one gauge means the understanding of the process and the
power of the model by using it to predict some periods of time when the land use conditions are known. This is then used as a test for validation.
The first is called ‘validate’, and it provides a comparative analysis on the
basis of the Kappa Index Analysis. Kappa is essentially a statement of proportional accuracy. Kappa is computed as:
